Work

Demand Estimation with Flexible Income Effect: An Application to Pass‐Through and Merger Analysis*

Year: 2024

Type: article

Abstract: This article proposes a semiparametric discrete choice model that incorporates a nonparametric specification for income effects. The model allows for the flexible estimation of demand curvature, which has significant implications for pricing and policy analysis in oligopolistic markets. Our estimation algorithm adopts a method of sieve approximation with shape restrictions in a nested fixed‐point algorithm. Applying this framework to the Japanese automobile market, we conduct a pass‐through analysis of feebates and merger simulations. Our model predicts a higher pass‐through rate and more significant merger effects than parametric demand models, highlighting the importance of flexibly estimating demand curvature.

Source: Journal of Industrial Economics

DOI: 10.1111/joie.12406

Authors: Shuhei Kaneko, Yuta Toyama

Institutions: University of California, Santa Barbara, Waseda University

Language: English

Topic: Merger and Competition Analysis

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,190

Funders: Waseda University, Japan Society for the Promotion of Science